Estimating the excess bed days and economic burden of healthcare-associated infections in Singapore public acute-care hospitals

2021 ◽  
pp. 1-4
Author(s):  
Yiying Cai ◽  
Indumathi Venkatachalam ◽  
Andrea L. Kwa ◽  
Paul A. Tambyah ◽  
Li Yang Hsu ◽  
...  
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Standard Deviation ◽  
Acute Care ◽  
Economic Burden ◽  
Healthcare Associated Infections ◽  
Healthcare Associated Infection ◽  
Bed Days ◽  
The Mean ◽  
Healthcare Associated

Abstract We estimated the annual bed days lost and economic burden of healthcare-associated infections to Singapore hospitals using Monte Carlo simulation. The mean (standard deviation) cost of a single healthcare-associated infection was S$1,809 (S$440) [or US$1,362 (US$331)]. This translated to annual lost bed days and economic burden of 55,978 (20,506) days and S$152.0 million (S$37.1 million) [or US$114.4 million (US$27.9 million)], respectively.

scholarly journals ANALISIS PENJADWALAN PROYEK GEDUNG BERTINGKAT DENGAN METODE PERT DAN M-PERT MENGGUNAKAN SIMULASI MONTE CARLO

2020 ◽  
Vol 3 (3) ◽  
pp. 533
Author(s):  
Josua Guntur Putra ◽  
Jane Sekarsari
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Standard Deviation ◽  
Research Method ◽  
Probabilistic Approach ◽  
Deterministic Scheduling ◽  
Work Duration ◽  
The Mean ◽  
Building Project ◽  
Story Building

One of the keys to success in construction execution is timeliness. In fact, construction is often late than originally planned. It’s caused by project scheduling uncertainty. Deterministic scheduling methods use data from previous projects to determine work duration. However, not every project has same work duration. The PERT method provides a probabilistic approach that can overcome these uncertainties, but it doesn’t account for the increase in duration due to parallel activities. In 2017, the PERT method was developed into the M-PERT method. The purpose of this study is to compare the mean duration and standard deviation of the overall project between PERT and M-PERT methods and compare them in Monte Carlo simulation. The research method used is to calculate the mean duration of the project with the PERT, M-PERT, and Monte Carlo simulation. The study was applied to a three-story building project. From the results of the study, the standard deviation obtained was 5.079 for the M-PERT method, 8.915 for the PERT method, and 5.25 for the Monte Carlo simulation. These results show the M-PERT method can provide closer results to computer simulation result than the PERT method. Small standard deviation value indicates the M-PERT method gives more accurate results.ABSTRAKSalah satu kunci keberhasilan dalam suatu pelaksanaan konstruksi adalah ketepatan waktu. Kenyataannya, pelaksanaan konstruksi sering mengalami keterlambatan waktu dari yang direncanakan. Hal ini disebabkan oleh ketidakpastian dalam merencanakan penjadwalan proyek. Metode penjadwalan yang bersifat deterministik menggunakan data dari proyek sebelumnya untuk menentukan durasi pekerjaan. Akan tetapi, tidak setiap proyek memiliki durasi pekerjaan yang sama. Metode PERT memberikan pendekatan probabilistik yang dapat mengatasi ketidakpastian tersebut, tetapi metode ini tidak memperhitungkan pertambahan durasi akibat adanya kegiatan yang berbentuk paralel. Pada tahun 2017, metode PERT dikembangkan menjadi metode M-PERT. Tujuan dari penelitian ini adalah membandingkan mean durasi dan standar deviasi proyek secara keseluruhan antara metode PERT dan M-PERT dan membandingkan kedua metode tersebut dalam simulasi Monte Carlo. Metode penelitian yang dilakukan adalah menghitung mean durasi proyek dengan metode PERT, M-PERT, dan simulasi Monte Carlo. Penelitian diterapkan pada proyek gedung bertingkat tiga. Dari hasil penelitian, nilai standar deviasi diperoleh sebesar 5,079 untuk metode M-PERT, 8,915 untuk metode PERT, dan 5,25 untuk simulasi Monte Carlo. Hasil ini menunjukan metode M-PERT dapat memberikan hasil yang lebih mendekati hasil simulasi komputer daripada metode PERT. Nilai standar deviasi yang kecil menunjukan metode M-PERT memberikan hasil yang lebih akurat.

Economic burden of antibiotic treatment of healthcare-associated infections at a tertiary care hospital ICU in Goa, India

2016 ◽  
Vol 47 (3) ◽  
pp. 197-201 ◽  
Author(s):  
Devika D Misal ◽  
Saleel V Maulingkar ◽  
Sushma Bhonsle
Keyword(s):  
Antibiotic Treatment ◽  
Economic Burden ◽  
Tertiary Care ◽  
Drug Expenditure ◽  
Healthcare Associated Infections ◽  
Care Hospital ◽  
The Mean ◽  
Antibiotic Cost ◽  
Healthcare Associated ◽  
Infection Control Guidelines

Antibiotics to treat healthcare-associated infections (HCAIs) contribute to a substantial proportion of drug expenditure in intensive care units (ICUs). Our study aimed to determine the common HCAIs in our hospital ICU, to assess the antibiotics prescribed and the mean antibiotic cost per HCAI. All adult patients, admitted to the ICU over a 1-year period, were included in the study. HCAIs were determined according to CDC definition. The incidence of HCAIs in the ICU was 16%. Ventilator associated pneumonia (50%) was the most common HCAI, followed by urinary tract infection (35.6%). The total cost of antibiotic treatment for HCAIs in ICU over a 1-year period was approximately Rs. 2 million (US$32,000); the mean antibiotic cost per HCAI was calculated as Rs. 17,000 (US$255). HCAIs in the ICU thus put a significant economic burden on the patient and the healthcare network and should be prevented by implementing recommended infection control guidelines.

scholarly journals Monte Carlo Simulation of the Formation of Snowflakes

2005 ◽  
Vol 62 (5) ◽  
pp. 1529-1544 ◽  
Author(s):  
Ken-ichi Maruyama ◽  
Yasushi Fujiyoshi
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Standard Deviation ◽  
Cross Section ◽  
Collision Cross Section ◽  
Initial Distribution ◽  
Sphere Model ◽  
Aggregate Model ◽  
Mean Diameter ◽  
The Mean

Abstract A stochastic microphysical model of snow aggregation that combines a simple aggregation model with a Monte Carlo method was developed. Explicit treatment of the shape of individual snowflakes in the new model facilitates examination of the structure of snowflakes and the relationships between the parameters of the generated snowflakes, such as mass versus diameter, in addition to comparisons with observations. In this study, complexities in the shape of snowflakes are successfully simulated, and the understanding of the evolution of their size distribution is advanced. The mean diameter of snow particles evolves more rapidly in the aggregate model than in the sphere model. However, growth rates of the aggregates greatly depend on the collision section of particles in aggregation. The mean mass of snowflakes in the aggregate model grows more slowly than the mass in the sphere model when the sum of the particle cross section is used as the collision cross section. The mean mass grows more quickly when a circle is used whose radius is the sum of the radii of two particles. Sensitivity experiments showed that aggregation also depends on the mean and standard deviation of the initial distribution, and on the density of constituent particles.

scholarly journals Indirect Versus Direct Standardization Methods for Reporting Healthcare-Associated Infections: An Analysis of Central Line–Associated Bloodstream Infections in Maryland

2017 ◽  
Vol 38 (8) ◽  
pp. 989-992 ◽  
Author(s):  
Lyndsay M. O’Hara ◽  
Max Masnick ◽  
Surbhi Leekha ◽  
Sarah S. Jackson ◽  
Natalia Blanco ◽  
...  
Keyword(s):  
Bloodstream Infection ◽  
Acute Care ◽  
Bloodstream Infections ◽  
Acute Care Hospitals ◽  
Central Line ◽  
Healthcare Associated Infections ◽  
Healthcare Associated Infection ◽  
Healthcare Associated ◽  
Direct Standardization ◽  
Standardization Methods

Whether healthcare-associated infection data should be presented using indirect (current CMS/CDC methodology) or direct standardization remains controversial. We applied both methods to central-line–associated bloodstream infection data from 45 acute-care hospitals in Maryland from 2012 to 2014. We found that the 2 methods generate different hospital rankings with payment implications.Infect Control Hosp Epidemiol 2017;38:989–992

Bearing-capacity prediction of spatially random c – ϕ soils

2003 ◽  
Vol 40 (1) ◽  
pp. 54-65 ◽  
Author(s):  
G A Fenton ◽  
D V Griffiths
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Standard Deviation ◽  
Bearing Capacity ◽  
Soil Surface ◽  
Element Analysis ◽  
Worst Case ◽  
Random Field Theory ◽  
Out Of Plane ◽  
The Mean

Soils with spatially varying shear strengths are modeled using random field theory and elasto-plastic finite element analysis to evaluate the extent to which spatial variability and cross-correlation in soil properties (c and ϕ) affect bearing capacity. The analysis is two dimensional, corresponding to a strip footing with infinite correlation length in the out-of-plane direction, and the soil is assumed to be weightless with footing placed on the soil surface. Theoretical predictions of the mean and standard deviation of bearing capacity, for the case where c and ϕ are independent, are derived using a geometric averaging model and then verified via Monte Carlo simulation. The standard deviation prediction is found to be quite accurate, while the mean prediction is found to require some additional semi-empirical adjustment to give accurate results for "worst case" correlation lengths. Combined, the theory can be used to estimate the probability of bearing-capacity failure, but also sheds light on the stochastic behaviour of foundation bearing failure.Key words: bearing capacity, probability, random fields, geometric averaging, c–ϕ soil, Monte Carlo simulation.

Mycobacteriosis as a Healthcare-Associated Infection: A Review of Epidemiologic Studies

2020 ◽  
pp. 37-41
Author(s):  
IV Petrov ◽  
TKh Amirova ◽  
LV Petrova ◽  
FS Petrova
Keyword(s):  
Skin Diseases ◽  
Nontuberculous Mycobacteria ◽  
Clinical Manifestations ◽  
Mycobacterial Infection ◽  
Epidemiologic Studies ◽  
Health Facilities ◽  
Water Supply Systems ◽  
Healthcare Associated Infections ◽  
Healthcare Associated Infection ◽  
Healthcare Associated

Introduction: Healthcare-associated infections are of great socio-economic importance and are characterized by a large number of different pathogens. Nontuberculous mycobacteria are ubiquitous microorganisms that can circulate in a medical organization. The purpose of this review of epidemiologic studies was to establish the main features of mycobacteriosis as a healthcare-associated infection, taking into account the significance of the results and the compliance of the reviewed studies with the criteria of evidence-based medicine. Methods: We did a key word search for “nontuberculous mycobacteria”, “healthcare-associated infections”, and “mycobacteriosis” in several electronic bibliographic databases including Web of Science, PubMed, eLIBRARY, and ResearchGate and selected 127 out of 342 search results. Having analyzed the selected articles, we decided to include 34 of them in this study according to the topic of work. We established that nontuberculous mycobacteria can be found in various objects of health facilities, e.g. water supply systems, medical products and equipment. We also found that mycobacterial infection of nosocomial etiology could have various clinical manifestations (arthritis, keratitis, circulatory and skin diseases, etc.) determined by various aspects, such as heterogeneity of the group of nontuberculous mycobacteria, portals of entry (surgical procedures on various organs and systems of the human body, etc.), pathways of exposure and transmission factors. Resistance of nontuberculous mycobacteria to a number of disinfectants is a special question defining the importance of profound research in terms of ensuring sanitary and anti-epidemic (disinfection) safety within health facilities. Conclusions: Our findings indicate that mycobacterial infection can be considered as a healthcare-associated infection requiring an in-depth assessment from various perspectives including a microbiological monitoring of medical objects, statistical accounting of nosocomial infections, and clinical alertness in the diagnosis of mycobacteriosis by attending physicians and bacteriologists, etc.

scholarly journals Pathogens Associated With Repeat Versus Single Central-Line–Associated Bloodstream Infections, Acute-Care Hospitals, NHSN

2020 ◽  
Vol 41 (S1) ◽  
pp. s343-s344
Author(s):  
Margaret A. Dudeck ◽  
Katherine Allen-Bridson ◽  
Jonathan R. Edwards
Keyword(s):  
Acute Care ◽  
National Level ◽  
Bloodstream Infections ◽  
Acute Care Hospitals ◽  
Central Line ◽  
Patient Specific ◽  
Healthcare Associated Infections ◽  
Healthcare Associated ◽  
Repeat Infection ◽  
Single Versus

Background: The NHSN is the nation’s largest surveillance system for healthcare-associated infections. Since 2011, acute-care hospitals (ACHs) have been required to report intensive care unit (ICU) central-line–associated bloodstream infections (CLABSIs) to the NHSN pursuant to CMS requirements. In 2015, this requirement included general medical, surgical, and medical-surgical wards. Also in 2015, the NHSN implemented a repeat infection timeframe (RIT) that required repeat CLABSIs, in the same patient and admission, to be excluded if onset was within 14 days. This analysis is the first at the national level to describe repeat CLABSIs. Methods: Index CLABSIs reported in ACH ICUs and select wards during 2015–2108 were included, in addition to repeat CLABSIs occurring at any location during the same period. CLABSIs were stratified into 2 groups: single and repeat CLABSIs. The repeat CLABSI group included the index CLABSI and subsequent CLABSI(s) reported for the same patient. Up to 5 CLABSIs were included for a single patient. Pathogen analyses were limited to the first pathogen reported for each CLABSI, which is considered to be the most important cause of the event. Likelihood ratio χ2 tests were used to determine differences in proportions. Results: Of the 70,214 CLABSIs reported, 5,983 (8.5%) were repeat CLABSIs. Of 3,264 nonindex CLABSIs, 425 (13%) were identified in non-ICU or non-select ward locations. Staphylococcus aureus was the most common pathogen in both the single and repeat CLABSI groups (14.2% and 12%, respectively) (Fig. 1). Compared to all other pathogens, CLABSIs reported with Candida spp were less likely in a repeat CLABSI event than in a single CLABSI event (P < .0001). Insertion-related organisms were more likely to be associated with single CLABSIs than repeat CLABSIs (P < .0001) (Fig. 2). Alternatively, Enterococcus spp or Klebsiella pneumoniae and K. oxytoca were more likely to be associated with repeat CLABSIs than single CLABSIs (P < .0001). Conclusions: This analysis highlights differences in the aggregate pathogen distributions comparing single versus repeat CLABSIs. Assessing the pathogens associated with repeat CLABSIs may offer another way to assess the success of CLABSI prevention efforts (eg, clean insertion practices). Pathogens such as Enterococcus spp and Klebsiella spp demonstrate a greater association with repeat CLABSIs. Thus, instituting prevention efforts focused on these organisms may warrant greater attention and could impact the likelihood of repeat CLABSIs. Additional analysis of patient-specific pathogens identified in the repeat CLABSI group may yield further clarification.Funding: NoneDisclosures: None

Rigorous time-domain analysis of statistically oriented graphene sheet fluctuations

2017 ◽  
Vol 36 (5) ◽  
pp. 1351-1363 ◽  
Author(s):  
Athanasios N. Papadimopoulos ◽  
Stamatios A. Amanatiadis ◽  
Nikolaos V. Kantartzis ◽  
Theodoros T. Zygiridis ◽  
Theodoros D. Tsiboukis
Keyword(s):  
Monte Carlo ◽  
Standard Deviation ◽  
Finite Difference ◽  
Surface Waves ◽  
Time Domain ◽  
Finite Difference Time Domain ◽  
Mean Value ◽  
Content Type ◽  
The Mean ◽  
Difference Time

Purpose Important statistical variations are likely to appear in the propagation of surface plasmon polariton waves atop the surface of graphene sheets, degrading the expected performance of real-life THz applications. This paper aims to introduce an efficient numerical algorithm that is able to accurately and rapidly predict the influence of material-based uncertainties for diverse graphene configurations. Design/methodology/approach Initially, the surface conductivity of graphene is described at the far infrared spectrum and the uncertainties of its main parameters, namely, the chemical potential and the relaxation time, on the propagation properties of the surface waves are investigated, unveiling a considerable impact. Furthermore, the demanding two-dimensional material is numerically modeled as a surface boundary through a frequency-dependent finite-difference time-domain scheme, while a robust stochastic realization is accordingly developed. Findings The mean value and standard deviation of the propagating surface waves are extracted through a single-pass simulation in contrast to the laborious Monte Carlo technique, proving the accomplished high efficiency. Moreover, numerical results, including graphene’s surface current density and electric field distribution, indicate the notable precision, stability and convergence of the new graphene-based stochastic time-domain method in terms of the mean value and the order of magnitude of the standard deviation. Originality/value The combined uncertainties of the main parameters in graphene layers are modeled through a high-performance stochastic numerical algorithm, based on the finite-difference time-domain method. The significant accuracy of the numerical results, compared to the cumbersome Monte Carlo analysis, renders the featured technique a flexible computational tool that is able to enhance the design of graphene THz devices due to the uncertainty prediction.

scholarly journals Bed-days and costs associated with the inpatient burden of healthcare-associated infection in the UK

2021 ◽  
Vol 114 ◽  
pp. 43-50 ◽  
Author(s):  
S. Manoukian ◽  
S. Stewart ◽  
N. Graves ◽  
H. Mason ◽  
C. Robertson ◽  
...  
Keyword(s):  
Healthcare Associated Infection ◽  
Bed Days ◽  
The Uk ◽  
Healthcare Associated
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